• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권4호
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• pp.327-332
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• 2005

We investigatea new fuzzy-neural networks-Hybrid Fuzzy set based polynomial Neural Networks (HFSPNN). These networks consist of genetically optimized multi-layer with two kinds of heterogeneous neurons thatare fuzzy set based polynomial neurons (FSPNs) and polynomial neurons (PNs). We have developed a comprehensive design methodology to determine the optimal structure of networks dynamically. The augmented genetically optimized HFSPNN (namely gHFSPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional HFPNN. The GA-based design procedure being applied at each layer of gHFSPNN leads to the selection leads to the selection of preferred nodes (FSPNs or PNs) available within the HFSPNN. In the sequel, the structural optimization is realized via GAs, whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gHFSPNN is quantified through experimentation where we use a number of modeling benchmarks synthetic and experimental data already experimented with in fuzzy or neurofuzzy modeling.

• Journal of Electrical Engineering and Technology
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• 제11권4호
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• pp.961-968
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• 2016

The non-uniform distribution of contamination on insulator surface has appreciable effects on flashover voltage, and corresponding researches are valuable for the better selection of outdoor insulation. In this paper, two typical types of porcelain and glass insulators which are widely used in ac lines were taken as the research subjects, and their corrections of AC flashover voltage under non-uniform pollution were studied. Besides, their flashover characteristics under different ratio (T/B) of top to bottom surface salt deposit density (SDD) were investigated, including the analysis of flashover voltage, surface pollution layer conductivity and critical leakage current. Test results gave the modified formulas for predicting flashover voltage of the two samples, which can be directly applied in the transmission line design. Also, the analysis delivered that, the basic reason why the flashover voltage increases with the decrease of T/B, is due to the decrease of equivalent surface conductivity of the whole surface and the decrease of critical leakage current. This research will be of certain value in providing references for outdoor insulation selection, as well as in proposing more information for revealing pollution flashover mechanism.

• 방송공학회논문지
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• 제24권4호
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• pp.613-622
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• 2019

코드북을 이용하는 폐루프 MISO 시스템에서 시간 상관성을 이용한 차분 코드북 설계 방법을 제안한다. 단일계층 코드북의 코드워드 인자들은 위상 성운의 집합 중에서 선택된다. 기존의 코드워드 선택 식에서는 코드워드들을 구면의 캡들이라 가정하고 서로의 각도를 사인 법칙을 이용하여 구하였으나, 본 논문에서는 피타고라스 법칙을 이용하는 새로운 방법을 이용하여 계산식을 간소화 시키는 식을 제안한다. 그리고 선택되는 코드워드간의 상관 계수 즉, 위상차의 변화를 추적하여 2 개의 코드북 중에 최적의 코드북을 적응적으로 선택하는 방법을 제안한다. Monte-Carlo 컴퓨터 시뮬레이션을 통해 제안하는 코드북의 성능을 검증한다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.363-363
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• 2023

Artificial Neural Networks (ANN) is a powerful tool for addressing various practical problems and it has been extensively applied in areas of water resources. In this study, Artificial Neural Networks (ANNs) were developed for flood forecasting at specific locations on the Han River. The Partial Mutual Information (PMI) technique was used to select input variables for ANNs that are neither over-specified nor under-specified while adequately describing the underlying input-output relationships. Historical observations including discharges at the Paldang Dam, flows from tributaries, water levels at the Paldang Bridge, Banpo Bridge, Hangang Bridge, and Junryu gauge station, and time derivatives of the observed water levels were considered as input candidates. Lagged variables from current time t to the previous five hours were assumed to be sufficient in this study. A three-layer neural network with one hidden layer was used and the neural network was optimized by selecting the optimal number of hidden neurons given the selected inputs. Given an ANN architecture, the weights and biases of the network were determined in the model training. The use of PMI-based input variable selection and optimized ANNs for different sites were proven to successfully predict water levels during flood periods.

• Asia pacific journal of information systems
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• 제30권1호
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• pp.31-52
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• 2020

Stock markets are popular investment avenues to people who plan to receive premium returns compared to other financial instruments, but they are highly volatile and risky due to the complex financial dynamics and poor understanding of the market forces involved in the price determination. A system that can forecast, predict the stock prices and automatically create a portfolio of top performing stocks is of great value to individual investors who do not have sufficient knowledge to understand the complex dynamics involved in evaluating and predicting stock prices. In this paper the authors propose a Stock prediction, Portfolio Generation and Selection model based on Machine learning algorithms, Artificial neural networks (ANNs) are used for stock price prediction, Mathematical and Statistical techniques are used for Portfolio generation and Un-Supervised Machine learning based on K-Means Clustering algorithms are used for Portfolio Evaluation and Selection which take in to account the Portfolio Return and Risk in to consideration. The model presented here is limited to predicting stock prices on a long term basis as the inputs to the model are based on fundamental attributes and intrinsic value of the stock. The results of this study are quite encouraging as the stock prediction models are able predict stock prices at least a financial quarter in advance with an accuracy of around 90 percent and the portfolio selection classifiers are giving returns in excess of average market returns.

• Journal of Astronomy and Space Sciences
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• 제32권2호
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• pp.137-140
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• 2015

The results of the study of ionospheric variations in the summer months of 1998-2002 at an ionospheric station of vertical sounding "Petropavlovsk-Kamchatsky" are presented. Anomalous variations of virtual sporadic-E height (h'Es), Es blanketing frequency (fbEs), and the critical frequency of the ionospheric F2 layer (foF2) (which can be attributed to the possible earthquake precursors) are selected. The high efficiency of the selection of ionospheric earthquake precursors based on the several parameters of Es and F2 layers is shown. The empirical dependence, which reflects the connection between the lead-time of the earthquake moment, the distance to the epicenter from the observation point, and the magnitude of the earthquake are obtained. This empirical dependence is consistent with the results of the detection of earthquake precursors by measuring the physical parameters of the Earth's crust in the same region.

• ETRI Journal
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• 제28권6호
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• pp.709-720
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• 2006

In this paper, we suggest a simple and efficient multiple-forwarder-based file distribution method which can work with a tree-based application layer multicast. Existing multiple-forwarder approaches require high control overhead. The proposed method exploits the assumption that receivers join a session at different times. In tree-based application layer multicast, a set of data packets is delivered from its parent after a receiver has joined but before the next receiver joins without overlapping that of other receivers. The proposed method selects forwarders from among the preceding receivers and the forwarder forwards data packets from the non-overlapping data packet set. Three variations of forwarder selection algorithms are proposed. The impact of the proposed algorithms is evaluated using numerical analysis. A performance evaluation using PlanetLab, a global area overlay testbed, shows that the proposed method enhances throughput while maintaining the data packet duplication ratio and control overhead significantly lower than the existing method, Bullet.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.240-242
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• 2007

The game theoretic analysis in wireless networks can be classified into the jamming game of the physical layer, the multiple access game of the medium access layer, the forwarder's dilemma and joint packet forwarding game of the network layer, and etc. In this paper, the game theoretic analysis about the multiple access game that selfish nodes exist in the IEEE 802.11 DCF(Distributed Coordination Function) wireless networks is addressed. In this' wireless networks, the modeling of the CSMA/CA protocol based DCF, the utility or payoff function calculation of the game, the system optimization (using optimization theory or convex optimization), and selection of Pareto-optimality and Nash Equilibrium in game strategies are the important elements for analyzing how nodes are operated in the steady state of system. Finally, the main issues about the game theory in the wireless network are introduced.

• 비파괴검사학회지
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• 제21권4호
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• pp.391-397
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• 2001

비균질 적층 구조물에서의 유도초음파 전파는 이론적 분산성에 기초하여 실험적으로 규명된다. 이는 입사각도와 주파수의 적절한 선택은 적층 구조물에서의 유도초음파 발생에 중요하나는 깃을 드러낸다. 이론적 분산성은 접착층 두께와 층 두께, 물성치에 크게 의존한다. 실험적으로 분산성의 변화를 관찰하므로 비균질 적층 구조물의 접착층 두께를 측정하는 것이 가능하였다.

• Journal of applied mathematics & informatics
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• 제9권1호
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• pp.101-124
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• 2002

The convergence rate of a numerical procedure barred on Schwarz Alternating Method (SAM) for solving elliptic boundary value problems (BVP's) depends on the selection of the interface conditions applied on the interior boundaries of the overlapping subdomains. It hee been observed that the Robin condition(mixed interface condition), controlled by a parameter, can optimize SAM's convergence rate. Since the convergence rate is very sensitive to the parameter, Tang[17] suggested another interface condition called over-determined interface condition. Based on the over-determined interface condition, we formulate the two-layer multi-parameterized SAM. For the SAM and the one-dimensional elliptic model BVP's, we determine analytically the optimal values of the parameters. For the two-dimensional elliptic BVP's , we also formulate the two-layer multi-parameterized SAM and suggest a choice of multi-parameter to produce good convergence rate .